Bibliographic record
Abstract
BackgroundThe BRIDgE platform is the Royal Marsden’s Trusted Research environment, which aims to transform clinical practice and improve outcomes for patients by enabling data analytics and AI development using real-world cancer data within secure, collaborative, cloud-based workspaces. This project evaluated the BRIDgE website against the new UK Health Data Research UK Transparency Standards, leading to changes to implement the following: Open Access Application form and Guidance (Standard 1), Transparent Access Process and Criteria (Standard 2), Clear website navigation (Standard 3), Consider Target Audience (Standard 4), Regular Review of Website Content (Standard 5), and Transparency of Data Use and Auditing (Standard 6). Our primary aim was to improve the content and sign posting so that patients and researchers would be better informed, resulting in increased website traffic and requests via our Contact Us page. MethodsInformation about the transparency project and the updates to the website were presented to a patient panel for feedback and a leaflet was co-designed with patient representatives. ResultsChanges included a new BRIDgE home page, which was re-designed to make navigation simpler and clearer, improved signposting, so both patients and researchers were aware of the sections meant for their consumption, such as the new Researchers’ Frequently Asked Questions (FAQ) page, which contained detailed instructions on how to request data, the governance workflow and costing structure. Finally, we expanded the Research Projects and Publications page, and added a Case Study from one of the Researchers, detailing their personal experience on the platform. ConclusionsWe anticipate that the impact of this project will be that patients will be more informed about Trusted Research Environments in general and what BRIDgE specifically enables in terms of innovative research and data security, leading to greater assurance for patients that their data is being used securely for their benefit. Researchers will get the benefit of the new FAQ page, which includes a great deal more information than was previously available about the platform, the data access methods, and the governance processes. We envisage that this will lead to more traffic on the site and a greater number of requests for information and workspaces via the Contact Us page. Finally, the patient leaflet will be the first time that patients in our waiting areas will be able to read about research informatics at the Royal Marsden and the work of our data scientists, in paper form. The resources developed using the funding from the transparency project are the revamped BRIDgE website https://www.cancerbrc.org/BRIDgE and (soon to be published) patient leaflet.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.059 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.090 | 0.017 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".